\section{Related works}\label{sec:related}
Two important related studies of our work are trust in communication network and trust in distributed artificial intelligent (DAI). Comparing with them,  trust in wireless network, p2p network are mostly provider-centered reputation or utility-driven individual view. They are too simple to express intrinsic concerns of actors in OSNs. On the other hand, the practices in DAI are often too complex and not operational for demands of online services, for example, the fundamental stimulate humans' psychological process by neural network is far from state of art.  Following paragraphs will list some of those models.

\para{Models based on centrality in Graph Theory:} This group of models finds the importance of a node in a network. However, Importance doesn't necessarily mean trustworthy. In OSNs, agents are independent with each other, authorities are significantly ignored. First such method for ranking the values of a nation's various industrial sectors in 1941, and the theory developed by Google Pagerank and HITS. Centrality theory is also the theory basis of original trust metric in advocate \cite{trust::leventrust}, as well as its extension, appleseed \cite{trust::appleseed}. The trusts reflected by those models generally are not based on personal perceive, it is based on network properties and system-level opinion. They also lack of dynamic from individual level to collective level, for example, in advogato, the trust values are spread from fixed sources, which is predefined based on existing knowledge. 

\para{Models based on utility } The second school of trust, is utility based trust. They reflect individual's view as well as reciprocity: by designing payment scheme of virtual currency, trust players will be rewarded, only if he plays trustworthy. Some former researches using utility are prove to be efficient, such as CONFIDENCE and TrustCent. However, researches found, individuals are not simply driven by utility, other factors, such as risk and competent, plays important roles as well. And more important, humans share atrium in social interactions. Therefore, in real world, trust is based on more complex intrinsic utilities which combines all or those factors. The most significant gold for us is to propose a model, which includes those factors without loss simplicity.

\para{Models based on perceiving behaviors:} This school of trust model focus on ``learn from past to predict future''.  It is heavily used in p2p and Wireless network. Our model can be generalized as this type. While the common difficulty for behavior perceiving is high cost and availability of informations. In OSNs, only limited insight each agent has. The global information is unavailable in normal situation. Our work distinguishes others in that our heuristic combines factors of human cognitive process: short-term and long-term memory, intrinsic utility, weighted propagation, and reciprocation. 